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Foreground extraction using iterated graph cuts

机译:使用迭代图切割进行前景提取

摘要

Techniques are disclosed to provide more efficient and improved extraction of a portion of a scene without requiring excessive user interaction. More particularly, the extraction may be achieved by using iterated graph cuts. In an implementation, a method includes segmenting an image into a foreground portion and a background portion (e.g., where an object or desired portion to be extracted is present in the foreground portion). The method determines the properties corresponding to the foreground and background portions of the image. Distributions may be utilized to model the foreground and background properties. The properties may be color in one implementation and the distributions may be a Gaussian Mixture Model in another implementation. The foreground and background properties are updated based on the portions. And, the foreground and background portions are updated based on the updated foreground and background properties.
机译:公开了在不需要过多用户交互的情况下提供对场景的一部分的更有效和改进的提取的技术。更具体地,可以通过使用迭代图切割来实现提取。在一种实现中,一种方法包括将图像分割成前景部分和背景部分(例如,在前景部分中存在要提取的对象或期望部分的地方)。该方法确定对应于图像的前景和背景部分的属性。分布可用于对前景和背景属性建模。在一个实现中,属性可以是颜色,而在另一个实现中,分布可以是高斯混合模型。前景和背景属性会根据这些部分进行更新。并且,基于更新的前景和背景属性来更新前景和背景部分。

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